Overview

Brought to you by YData

Dataset statistics

Number of variables25
Number of observations10105
Missing cells7601
Missing cells (%)3.0%
Duplicate rows105
Duplicate rows (%)1.0%
Total size in memory3.7 MiB
Average record size in memory388.5 B

Variable types

Numeric20
Categorical4
DateTime1

Alerts

Dataset has 105 (1.0%) duplicate rowsDuplicates
num1 has 310 (3.1%) missing values Missing
num2 has 313 (3.1%) missing values Missing
num3 has 312 (3.1%) missing values Missing
num4 has 316 (3.1%) missing values Missing
num5 has 305 (3.0%) missing values Missing
num6 has 346 (3.4%) missing values Missing
num7 has 285 (2.8%) missing values Missing
num8 has 328 (3.2%) missing values Missing
num9 has 303 (3.0%) missing values Missing
num10 has 311 (3.1%) missing values Missing
num11 has 302 (3.0%) missing values Missing
num12 has 298 (2.9%) missing values Missing
num13 has 287 (2.8%) missing values Missing
num14 has 298 (2.9%) missing values Missing
num15 has 312 (3.1%) missing values Missing
num16 has 311 (3.1%) missing values Missing
num17 has 301 (3.0%) missing values Missing
num18 has 302 (3.0%) missing values Missing
num19 has 305 (3.0%) missing values Missing
num20 has 291 (2.9%) missing values Missing
cat1 has 324 (3.2%) missing values Missing
cat2 has 277 (2.7%) missing values Missing
cat3 has 310 (3.1%) missing values Missing
date has 251 (2.5%) missing values Missing
class has 303 (3.0%) missing values Missing
num1 is highly skewed (γ1 = 31.03946193) Skewed
num3 is highly skewed (γ1 = 30.97264746) Skewed
num4 is highly skewed (γ1 = 31.01732662) Skewed
num9 is highly skewed (γ1 = 30.88371776) Skewed

Reproduction

Analysis started2025-05-06 07:02:01.350623
Analysis finished2025-05-06 07:02:03.152594
Duration1.8 second
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

num1
Real number (ℝ)

Missing  Skewed 

Distinct9683
Distinct (%)98.9%
Missing310
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean1.1881683
Minimum-7.3123638
Maximum997.29283
Zeros0
Zeros (%)0.0%
Negative4607
Negative (%)45.6%
Memory size79.1 KiB
2025-05-06T10:02:03.198328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-7.3123638
5-th percentile-3.3569112
Q1-1.2895834
median0.15809625
Q31.6176323
95-th percentile3.7824435
Maximum997.29283
Range1004.6052
Interquartile range (IQR)2.9072157

Descriptive statistics

Standard deviation31.918392
Coefficient of variation (CV)26.863527
Kurtosis966.08406
Mean1.1881683
Median Absolute Deviation (MAD)1.4545565
Skewness31.039462
Sum11638.109
Variance1018.7838
MonotonicityNot monotonic
2025-05-06T10:02:03.272063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
997.2928281 10
 
0.1%
-1.14194239 2
 
< 0.1%
-3.762070131 2
 
< 0.1%
-0.03842931424 2
 
< 0.1%
2.189606813 2
 
< 0.1%
1.545131281 2
 
< 0.1%
-1.021608434 2
 
< 0.1%
4.144942057 2
 
< 0.1%
-1.714344782 2
 
< 0.1%
0.4271802674 2
 
< 0.1%
Other values (9673) 9767
96.7%
(Missing) 310
 
3.1%
ValueCountFrequency (%)
-7.31236376 1
< 0.1%
-6.563736118 1
< 0.1%
-6.563579337 1
< 0.1%
-6.555985063 1
< 0.1%
-6.544627166 1
< 0.1%
-6.48529233 1
< 0.1%
-6.403680065 1
< 0.1%
-6.396776866 1
< 0.1%
-6.373758417 1
< 0.1%
-6.351361276 1
< 0.1%
ValueCountFrequency (%)
997.2928281 10
0.1%
9.972928281 1
 
< 0.1%
9.466578088 1
 
< 0.1%
8.344125576 1
 
< 0.1%
8.169416662 1
 
< 0.1%
7.666668742 1
 
< 0.1%
7.515964994 1
 
< 0.1%
7.400754338 1
 
< 0.1%
7.329332421 1
 
< 0.1%
7.265291604 1
 
< 0.1%

num2
Real number (ℝ)

Missing 

Distinct9688
Distinct (%)98.9%
Missing313
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean0.84617923
Minimum-7.3769124
Maximum9.2400353
Zeros0
Zeros (%)0.0%
Negative3361
Negative (%)33.3%
Memory size79.1 KiB
2025-05-06T10:02:03.351792image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-7.3769124
5-th percentile-2.7282262
Q1-0.58448487
median0.87217475
Q32.3026682
95-th percentile4.3823492
Maximum9.2400353
Range16.616948
Interquartile range (IQR)2.887153

Descriptive statistics

Standard deviation2.1510098
Coefficient of variation (CV)2.5420263
Kurtosis-0.00087156137
Mean0.84617923
Median Absolute Deviation (MAD)1.4447592
Skewness-0.061639475
Sum8285.787
Variance4.6268432
MonotonicityNot monotonic
2025-05-06T10:02:03.427779image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.597323758 2
 
< 0.1%
5.460773597 2
 
< 0.1%
1.083378115 2
 
< 0.1%
2.456460191 2
 
< 0.1%
1.701629974 2
 
< 0.1%
-1.597446262 2
 
< 0.1%
-2.744818434 2
 
< 0.1%
-0.6176758203 2
 
< 0.1%
0.6464488276 2
 
< 0.1%
2.060908777 2
 
< 0.1%
Other values (9678) 9772
96.7%
(Missing) 313
 
3.1%
ValueCountFrequency (%)
-7.37691236 1
< 0.1%
-6.570573273 1
< 0.1%
-6.54126208 1
< 0.1%
-6.346764751 1
< 0.1%
-6.188811248 1
< 0.1%
-5.865134027 1
< 0.1%
-5.860873977 1
< 0.1%
-5.785223928 1
< 0.1%
-5.782124824 1
< 0.1%
-5.743186105 1
< 0.1%
ValueCountFrequency (%)
9.240035299 1
< 0.1%
8.455449101 1
< 0.1%
7.982371321 1
< 0.1%
7.862998402 1
< 0.1%
7.7565944 1
< 0.1%
7.723683221 1
< 0.1%
7.685764334 1
< 0.1%
7.593112205 1
< 0.1%
7.391553835 1
< 0.1%
7.332245295 1
< 0.1%

num3
Real number (ℝ)

Missing  Skewed 

Distinct9679
Distinct (%)98.8%
Missing312
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean1.8305977
Minimum-5.9626889
Maximum796.4647
Zeros0
Zeros (%)0.0%
Negative2950
Negative (%)29.2%
Memory size79.1 KiB
2025-05-06T10:02:03.507861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-5.9626889
5-th percentile-2.218118
Q1-0.28452615
median1.0080317
Q32.3489874
95-th percentile4.2569986
Maximum796.4647
Range802.42739
Interquartile range (IQR)2.6335135

Descriptive statistics

Standard deviation25.482617
Coefficient of variation (CV)13.920381
Kurtosis963.24448
Mean1.8305977
Median Absolute Deviation (MAD)1.3197761
Skewness30.972647
Sum17927.043
Variance649.36378
MonotonicityNot monotonic
2025-05-06T10:02:03.586054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
796.4646985 10
 
0.1%
1.254461308 2
 
< 0.1%
-0.1780485179 2
 
< 0.1%
2.474184061 2
 
< 0.1%
-1.814226206 2
 
< 0.1%
3.598225724 2
 
< 0.1%
1.321949015 2
 
< 0.1%
0.6626729516 2
 
< 0.1%
2.362027641 2
 
< 0.1%
1.819984674 2
 
< 0.1%
Other values (9669) 9765
96.6%
(Missing) 312
 
3.1%
ValueCountFrequency (%)
-5.962688947 1
< 0.1%
-5.896689262 1
< 0.1%
-5.742192193 1
< 0.1%
-5.648760222 1
< 0.1%
-5.624561486 1
< 0.1%
-5.608265163 1
< 0.1%
-5.599270369 1
< 0.1%
-5.57520416 1
< 0.1%
-5.553583512 1
< 0.1%
-5.550637471 1
< 0.1%
ValueCountFrequency (%)
796.4646985 10
0.1%
7.964646985 1
 
< 0.1%
7.919024042 1
 
< 0.1%
7.907376429 1
 
< 0.1%
7.715011103 1
 
< 0.1%
7.452340134 1
 
< 0.1%
7.442576754 1
 
< 0.1%
7.274773862 1
 
< 0.1%
7.263014677 1
 
< 0.1%
7.257786471 1
 
< 0.1%

num4
Real number (ℝ)

Missing  Skewed 

Distinct9678
Distinct (%)98.9%
Missing316
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean1.1298631
Minimum-7.8521636
Maximum1046.711
Zeros0
Zeros (%)0.0%
Negative4843
Negative (%)47.9%
Memory size79.1 KiB
2025-05-06T10:02:03.665610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-7.8521636
5-th percentile-3.799837
Q1-1.5443091
median0.033074395
Q31.6507387
95-th percentile3.9519205
Maximum1046.711
Range1054.5632
Interquartile range (IQR)3.1950479

Descriptive statistics

Standard deviation33.518581
Coefficient of variation (CV)29.666056
Kurtosis964.96649
Mean1.1298631
Median Absolute Deviation (MAD)1.5976514
Skewness31.017327
Sum11060.23
Variance1123.4953
MonotonicityNot monotonic
2025-05-06T10:02:03.754311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1046.710991 10
 
0.1%
1.951753182 2
 
< 0.1%
-0.8418140499 2
 
< 0.1%
1.605733197 2
 
< 0.1%
5.062682145 2
 
< 0.1%
1.026487467 2
 
< 0.1%
2.429784922 2
 
< 0.1%
1.633288942 2
 
< 0.1%
-0.3511915268 2
 
< 0.1%
-0.7875682826 2
 
< 0.1%
Other values (9668) 9761
96.6%
(Missing) 316
 
3.1%
ValueCountFrequency (%)
-7.852163578 1
< 0.1%
-7.819157095 1
< 0.1%
-7.713121707 1
< 0.1%
-7.132055837 1
< 0.1%
-7.092338561 1
< 0.1%
-7.068260833 1
< 0.1%
-7.067210192 1
< 0.1%
-6.846934671 1
< 0.1%
-6.613817945 1
< 0.1%
-6.534161681 1
< 0.1%
ValueCountFrequency (%)
1046.710991 10
0.1%
10.46710991 1
 
< 0.1%
9.017912059 1
 
< 0.1%
8.614835518 1
 
< 0.1%
7.536701199 1
 
< 0.1%
7.508108201 1
 
< 0.1%
7.43867958 1
 
< 0.1%
7.410434768 1
 
< 0.1%
7.337693534 1
 
< 0.1%
7.329656236 1
 
< 0.1%

num5
Real number (ℝ)

Missing 

Distinct9699
Distinct (%)99.0%
Missing305
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean1.0372686
Minimum-7.4785625
Maximum10.057636
Zeros0
Zeros (%)0.0%
Negative3056
Negative (%)30.2%
Memory size79.1 KiB
2025-05-06T10:02:03.844680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-7.4785625
5-th percentile-2.4425124
Q1-0.36387822
median1.0408825
Q32.4396996
95-th percentile4.5757228
Maximum10.057636
Range17.536199
Interquartile range (IQR)2.8035778

Descriptive statistics

Standard deviation2.1156057
Coefficient of variation (CV)2.0395929
Kurtosis0.046846093
Mean1.0372686
Median Absolute Deviation (MAD)1.4016265
Skewness0.01170869
Sum10165.232
Variance4.4757877
MonotonicityNot monotonic
2025-05-06T10:02:04.033844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.804517004 2
 
< 0.1%
-1.036697344 2
 
< 0.1%
2.767274146 2
 
< 0.1%
4.569061589 2
 
< 0.1%
0.5308667723 2
 
< 0.1%
2.117050604 2
 
< 0.1%
1.454130344 2
 
< 0.1%
2.671163247 2
 
< 0.1%
2.803058993 2
 
< 0.1%
-0.4165889244 2
 
< 0.1%
Other values (9689) 9780
96.8%
(Missing) 305
 
3.0%
ValueCountFrequency (%)
-7.478562542 1
< 0.1%
-6.89103447 1
< 0.1%
-6.24610309 1
< 0.1%
-6.033475472 1
< 0.1%
-5.994938651 1
< 0.1%
-5.958295283 1
< 0.1%
-5.731354407 1
< 0.1%
-5.695531135 1
< 0.1%
-5.651656641 1
< 0.1%
-5.575474603 1
< 0.1%
ValueCountFrequency (%)
10.05763619 1
< 0.1%
8.555827031 1
< 0.1%
8.239249239 1
< 0.1%
8.066946903 1
< 0.1%
7.942821585 1
< 0.1%
7.767821484 1
< 0.1%
7.758518144 1
< 0.1%
7.636304662 1
< 0.1%
7.513250599 1
< 0.1%
7.435607787 1
< 0.1%

num6
Real number (ℝ)

Missing 

Distinct9658
Distinct (%)99.0%
Missing346
Missing (%)3.4%
Infinite0
Infinite (%)0.0%
Mean-0.00082786538
Minimum-8.5955981
Maximum8.9543706
Zeros0
Zeros (%)0.0%
Negative4929
Negative (%)48.8%
Memory size79.1 KiB
2025-05-06T10:02:04.121215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-8.5955981
5-th percentile-3.8909139
Q1-1.6336231
median-0.032492456
Q31.5899049
95-th percentile4.0624492
Maximum8.9543706
Range17.549969
Interquartile range (IQR)3.223528

Descriptive statistics

Standard deviation2.4155977
Coefficient of variation (CV)-2917.8629
Kurtosis0.038791898
Mean-0.00082786538
Median Absolute Deviation (MAD)1.6141468
Skewness0.09154228
Sum-8.0791383
Variance5.835112
MonotonicityNot monotonic
2025-05-06T10:02:04.203083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-2.370915023 2
 
< 0.1%
-0.6997836878 2
 
< 0.1%
-3.048310678 2
 
< 0.1%
-0.5718078435 2
 
< 0.1%
-2.753353326 2
 
< 0.1%
1.014350571 2
 
< 0.1%
0.04970219899 2
 
< 0.1%
2.878089295 2
 
< 0.1%
0.7434625919 2
 
< 0.1%
-2.527258318 2
 
< 0.1%
Other values (9648) 9739
96.4%
(Missing) 346
 
3.4%
ValueCountFrequency (%)
-8.595598128 1
< 0.1%
-8.548382898 1
< 0.1%
-8.436286756 1
< 0.1%
-8.313929903 1
< 0.1%
-8.00630023 1
< 0.1%
-7.725281922 1
< 0.1%
-7.672669138 1
< 0.1%
-7.646480314 1
< 0.1%
-7.544214998 1
< 0.1%
-7.502329475 1
< 0.1%
ValueCountFrequency (%)
8.954370551 1
< 0.1%
8.242376314 1
< 0.1%
8.034487822 1
< 0.1%
8.022511251 1
< 0.1%
7.962377582 1
< 0.1%
7.950304755 1
< 0.1%
7.826991228 1
< 0.1%
7.699971049 1
< 0.1%
7.66396182 1
< 0.1%
7.623663923 1
< 0.1%

num7
Real number (ℝ)

Missing 

Distinct9721
Distinct (%)99.0%
Missing285
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean0.015090107
Minimum-7.2958929
Maximum9.7833807
Zeros0
Zeros (%)0.0%
Negative4947
Negative (%)49.0%
Memory size79.1 KiB
2025-05-06T10:02:04.278131image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-7.2958929
5-th percentile-3.6769972
Q1-1.4994572
median-0.026005632
Q31.5547591
95-th percentile3.7262713
Maximum9.7833807
Range17.079274
Interquartile range (IQR)3.0542163

Descriptive statistics

Standard deviation2.262934
Coefficient of variation (CV)149.96143
Kurtosis0.063174477
Mean0.015090107
Median Absolute Deviation (MAD)1.5214326
Skewness0.078895328
Sum148.18485
Variance5.1208705
MonotonicityNot monotonic
2025-05-06T10:02:04.362960image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-5.248414601 2
 
< 0.1%
4.07467902 2
 
< 0.1%
-1.649761017 2
 
< 0.1%
2.124867266 2
 
< 0.1%
-2.675983464 2
 
< 0.1%
1.863048074 2
 
< 0.1%
-1.36669988 2
 
< 0.1%
-0.7035905759 2
 
< 0.1%
1.962297755 2
 
< 0.1%
-2.216186809 2
 
< 0.1%
Other values (9711) 9800
97.0%
(Missing) 285
 
2.8%
ValueCountFrequency (%)
-7.295892865 1
< 0.1%
-7.21503977 1
< 0.1%
-7.183504927 1
< 0.1%
-7.110826169 1
< 0.1%
-7.081990083 1
< 0.1%
-7.078763576 1
< 0.1%
-6.942280581 1
< 0.1%
-6.833179484 1
< 0.1%
-6.826528823 1
< 0.1%
-6.781788029 1
< 0.1%
ValueCountFrequency (%)
9.783380741 1
< 0.1%
9.400690153 1
< 0.1%
8.730098354 1
< 0.1%
8.588431015 1
< 0.1%
8.358162841 1
< 0.1%
8.339991928 1
< 0.1%
7.972294532 1
< 0.1%
7.876971499 2
< 0.1%
7.851414642 1
< 0.1%
7.76851852 1
< 0.1%

num8
Real number (ℝ)

Missing 

Distinct9673
Distinct (%)98.9%
Missing328
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean0.18104832
Minimum-7.5761319
Maximum9.6805945
Zeros0
Zeros (%)0.0%
Negative4650
Negative (%)46.0%
Memory size79.1 KiB
2025-05-06T10:02:04.457736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-7.5761319
5-th percentile-3.4554048
Q1-1.418047
median0.1624197
Q31.6978231
95-th percentile4.0460642
Maximum9.6805945
Range17.256726
Interquartile range (IQR)3.1158701

Descriptive statistics

Standard deviation2.2643188
Coefficient of variation (CV)12.50671
Kurtosis-0.059558056
Mean0.18104832
Median Absolute Deviation (MAD)1.5588518
Skewness0.11300003
Sum1770.1094
Variance5.1271395
MonotonicityNot monotonic
2025-05-06T10:02:04.552219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.304273373 2
 
< 0.1%
0.04641748757 2
 
< 0.1%
-1.779020673 2
 
< 0.1%
1.573556909 2
 
< 0.1%
-0.5918159206 2
 
< 0.1%
0.4646871325 2
 
< 0.1%
-0.9262906113 2
 
< 0.1%
5.988346886 2
 
< 0.1%
0.1803020062 2
 
< 0.1%
0.6028130579 2
 
< 0.1%
Other values (9663) 9757
96.6%
(Missing) 328
 
3.2%
ValueCountFrequency (%)
-7.576131924 1
< 0.1%
-7.006741516 1
< 0.1%
-6.884227023 1
< 0.1%
-6.855723503 1
< 0.1%
-6.76953027 1
< 0.1%
-6.543652736 1
< 0.1%
-6.376341179 1
< 0.1%
-6.356079148 1
< 0.1%
-6.30605168 1
< 0.1%
-6.295054586 1
< 0.1%
ValueCountFrequency (%)
9.68059452 1
< 0.1%
9.534246473 1
< 0.1%
9.087571793 1
< 0.1%
8.608617853 1
< 0.1%
8.015759822 1
< 0.1%
7.688039168 1
< 0.1%
7.680545238 1
< 0.1%
7.461776352 1
< 0.1%
7.352800946 1
< 0.1%
7.335585279 1
< 0.1%

num9
Real number (ℝ)

Missing  Skewed 

Distinct9691
Distinct (%)98.9%
Missing303
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean0.63513455
Minimum-9.9195461
Maximum822.32793
Zeros0
Zeros (%)0.0%
Negative5014
Negative (%)49.6%
Memory size79.1 KiB
2025-05-06T10:02:04.645139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-9.9195461
5-th percentile-4.3451308
Q1-1.7296183
median-0.071488137
Q31.4782326
95-th percentile3.5157925
Maximum822.32793
Range832.24748
Interquartile range (IQR)3.2078508

Descriptive statistics

Standard deviation26.367423
Coefficient of variation (CV)41.514704
Kurtosis959.85828
Mean0.63513455
Median Absolute Deviation (MAD)1.5987397
Skewness30.883718
Sum6225.5889
Variance695.24099
MonotonicityNot monotonic
2025-05-06T10:02:04.724729image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
822.3279296 10
 
0.1%
2.67542621 2
 
< 0.1%
0.9429512423 2
 
< 0.1%
-1.96644269 2
 
< 0.1%
0.5115408031 2
 
< 0.1%
-1.10367006 2
 
< 0.1%
-0.9028993446 2
 
< 0.1%
-0.2873290345 2
 
< 0.1%
1.137951341 2
 
< 0.1%
8.223279296 2
 
< 0.1%
Other values (9681) 9774
96.7%
(Missing) 303
 
3.0%
ValueCountFrequency (%)
-9.919546055 1
< 0.1%
-9.28493376 1
< 0.1%
-9.216302026 1
< 0.1%
-8.726249954 1
< 0.1%
-8.723848037 1
< 0.1%
-8.489811575 1
< 0.1%
-8.350341343 1
< 0.1%
-8.300079428 1
< 0.1%
-8.274741256 1
< 0.1%
-7.998481242 1
< 0.1%
ValueCountFrequency (%)
822.3279296 10
0.1%
8.223279296 2
 
< 0.1%
7.021556172 1
 
< 0.1%
7.009912196 2
 
< 0.1%
6.751769865 1
 
< 0.1%
6.360897713 1
 
< 0.1%
6.249144828 2
 
< 0.1%
6.244753568 1
 
< 0.1%
6.178010622 1
 
< 0.1%
6.148826265 1
 
< 0.1%

num10
Real number (ℝ)

Missing 

Distinct9694
Distinct (%)99.0%
Missing311
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean1.0109434
Minimum-8.4744005
Maximum9.4094853
Zeros0
Zeros (%)0.0%
Negative3183
Negative (%)31.5%
Memory size79.1 KiB
2025-05-06T10:02:04.799946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-8.4744005
5-th percentile-2.7496463
Q1-0.49292786
median1.0283057
Q32.5249657
95-th percentile4.7237492
Maximum9.4094853
Range17.883886
Interquartile range (IQR)3.0178936

Descriptive statistics

Standard deviation2.2753277
Coefficient of variation (CV)2.2506974
Kurtosis0.11424932
Mean1.0109434
Median Absolute Deviation (MAD)1.5088296
Skewness-0.0084941246
Sum9901.1798
Variance5.1771162
MonotonicityNot monotonic
2025-05-06T10:02:04.877838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.655241535 2
 
< 0.1%
-3.133514013 2
 
< 0.1%
0.2332828447 2
 
< 0.1%
-3.483627402 2
 
< 0.1%
-1.411278438 2
 
< 0.1%
0.8633931366 2
 
< 0.1%
1.864092887 2
 
< 0.1%
1.165710271 2
 
< 0.1%
0.8225037937 2
 
< 0.1%
1.693222782 2
 
< 0.1%
Other values (9684) 9774
96.7%
(Missing) 311
 
3.1%
ValueCountFrequency (%)
-8.474400519 1
< 0.1%
-7.838425407 1
< 0.1%
-7.317612554 1
< 0.1%
-7.151876867 1
< 0.1%
-6.725668709 1
< 0.1%
-6.557973116 1
< 0.1%
-6.189789133 1
< 0.1%
-6.141414317 1
< 0.1%
-6.134575344 1
< 0.1%
-6.052963167 1
< 0.1%
ValueCountFrequency (%)
9.409485334 1
< 0.1%
9.219569149 1
< 0.1%
9.213225886 1
< 0.1%
9.197276595 1
< 0.1%
9.106317576 1
< 0.1%
9.075575822 1
< 0.1%
9.06377833 1
< 0.1%
8.81461661 1
< 0.1%
8.810777698 1
< 0.1%
8.768670463 1
< 0.1%

num11
Real number (ℝ)

Missing 

Distinct9702
Distinct (%)99.0%
Missing302
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean0.23688183
Minimum-8.4413767
Maximum11.470078
Zeros0
Zeros (%)0.0%
Negative4590
Negative (%)45.4%
Memory size79.1 KiB
2025-05-06T10:02:04.964489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-8.4413767
5-th percentile-3.7121102
Q1-1.4531099
median0.2122618
Q31.9118026
95-th percentile4.3386061
Maximum11.470078
Range19.911454
Interquartile range (IQR)3.3649125

Descriptive statistics

Standard deviation2.4554202
Coefficient of variation (CV)10.365591
Kurtosis-0.081304221
Mean0.23688183
Median Absolute Deviation (MAD)1.6856477
Skewness0.090170659
Sum2322.1525
Variance6.0290884
MonotonicityNot monotonic
2025-05-06T10:02:05.032752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.850094337 2
 
< 0.1%
-1.426881413 2
 
< 0.1%
3.118282777 2
 
< 0.1%
0.5097358511 2
 
< 0.1%
0.6064700441 2
 
< 0.1%
-0.2473657823 2
 
< 0.1%
4.937940685 2
 
< 0.1%
0.5042972321 2
 
< 0.1%
1.946722066 2
 
< 0.1%
1.989841912 2
 
< 0.1%
Other values (9692) 9783
96.8%
(Missing) 302
 
3.0%
ValueCountFrequency (%)
-8.441376676 1
< 0.1%
-7.549996761 1
< 0.1%
-7.390599308 1
< 0.1%
-7.369360581 1
< 0.1%
-7.277461483 1
< 0.1%
-7.275977672 1
< 0.1%
-6.909310717 1
< 0.1%
-6.904669152 1
< 0.1%
-6.897081535 1
< 0.1%
-6.879916889 1
< 0.1%
ValueCountFrequency (%)
11.47007776 1
< 0.1%
9.531949023 1
< 0.1%
9.082795093 1
< 0.1%
8.784376631 1
< 0.1%
8.29129215 1
< 0.1%
8.10187601 1
< 0.1%
8.056010528 1
< 0.1%
8.045480164 1
< 0.1%
8.02020033 1
< 0.1%
7.966841026 1
< 0.1%

num12
Real number (ℝ)

Missing 

Distinct9707
Distinct (%)99.0%
Missing298
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean0.17430295
Minimum-8.4797934
Maximum8.6573329
Zeros0
Zeros (%)0.0%
Negative4584
Negative (%)45.4%
Memory size79.1 KiB
2025-05-06T10:02:05.118981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-8.4797934
5-th percentile-3.8769069
Q1-1.4314522
median0.20848562
Q31.7796575
95-th percentile4.1092129
Maximum8.6573329
Range17.137126
Interquartile range (IQR)3.2111098

Descriptive statistics

Standard deviation2.4148968
Coefficient of variation (CV)13.854595
Kurtosis-0.0075479613
Mean0.17430295
Median Absolute Deviation (MAD)1.6043286
Skewness-0.053114187
Sum1709.3891
Variance5.8317267
MonotonicityNot monotonic
2025-05-06T10:02:05.199393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1.475675164 2
 
< 0.1%
-1.802082889 2
 
< 0.1%
-0.3089834132 2
 
< 0.1%
-0.2778661873 2
 
< 0.1%
4.494147012 2
 
< 0.1%
1.329273807 2
 
< 0.1%
1.732031064 2
 
< 0.1%
4.31581702 2
 
< 0.1%
1.640631949 2
 
< 0.1%
0.7108040291 2
 
< 0.1%
Other values (9697) 9787
96.9%
(Missing) 298
 
2.9%
ValueCountFrequency (%)
-8.479793361 1
< 0.1%
-8.292054567 1
< 0.1%
-8.267697205 1
< 0.1%
-7.848971609 1
< 0.1%
-7.658221389 1
< 0.1%
-7.654099825 1
< 0.1%
-7.594734097 1
< 0.1%
-7.577735611 1
< 0.1%
-7.577239976 1
< 0.1%
-7.52465122 1
< 0.1%
ValueCountFrequency (%)
8.657332872 1
< 0.1%
8.438782161 1
< 0.1%
8.219495891 1
< 0.1%
8.174192586 1
< 0.1%
8.098233681 1
< 0.1%
7.999122703 2
< 0.1%
7.902826477 1
< 0.1%
7.820662848 1
< 0.1%
7.76679497 1
< 0.1%
7.637218231 1
< 0.1%

num13
Real number (ℝ)

Missing 

Distinct9715
Distinct (%)99.0%
Missing287
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean0.98501651
Minimum-8.0498359
Maximum10.666849
Zeros0
Zeros (%)0.0%
Negative3309
Negative (%)32.7%
Memory size79.1 KiB
2025-05-06T10:02:05.265529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-8.0498359
5-th percentile-2.9162568
Q1-0.62456641
median0.97178637
Q32.5987128
95-th percentile4.8523199
Maximum10.666849
Range18.716685
Interquartile range (IQR)3.2232792

Descriptive statistics

Standard deviation2.3635929
Coefficient of variation (CV)2.3995464
Kurtosis-0.023535391
Mean0.98501651
Median Absolute Deviation (MAD)1.6113131
Skewness-0.011262467
Sum9670.8921
Variance5.5865712
MonotonicityNot monotonic
2025-05-06T10:02:05.350311image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.5284296783 2
 
< 0.1%
2.256002428 2
 
< 0.1%
0.8510723751 2
 
< 0.1%
-1.336924439 2
 
< 0.1%
-4.029109274 2
 
< 0.1%
0.8644186159 2
 
< 0.1%
2.138078814 2
 
< 0.1%
1.096990464 2
 
< 0.1%
1.988981271 2
 
< 0.1%
5.007806764 2
 
< 0.1%
Other values (9705) 9798
97.0%
(Missing) 287
 
2.8%
ValueCountFrequency (%)
-8.04983594 1
< 0.1%
-7.115874931 1
< 0.1%
-6.611262682 1
< 0.1%
-6.473855366 1
< 0.1%
-6.471074989 1
< 0.1%
-6.466262235 1
< 0.1%
-6.425083625 1
< 0.1%
-6.411940706 1
< 0.1%
-6.374605035 1
< 0.1%
-6.373285218 1
< 0.1%
ValueCountFrequency (%)
10.66684866 1
< 0.1%
9.401089533 1
< 0.1%
9.209535562 1
< 0.1%
9.129300648 1
< 0.1%
9.076719853 1
< 0.1%
8.977209205 1
< 0.1%
8.694023902 1
< 0.1%
8.536984281 1
< 0.1%
8.156853938 1
< 0.1%
8.134555134 1
< 0.1%

num14
Real number (ℝ)

Missing 

Distinct9704
Distinct (%)98.9%
Missing298
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean-1.0050422
Minimum-9.526823
Maximum8.4180821
Zeros0
Zeros (%)0.0%
Negative6807
Negative (%)67.4%
Memory size79.1 KiB
2025-05-06T10:02:05.433001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-9.526823
5-th percentile-4.2734006
Q1-2.3083912
median-0.98405739
Q30.31787494
95-th percentile2.1919918
Maximum8.4180821
Range17.944905
Interquartile range (IQR)2.6262661

Descriptive statistics

Standard deviation1.984347
Coefficient of variation (CV)-1.9743918
Kurtosis0.29605029
Mean-1.0050422
Median Absolute Deviation (MAD)1.3133362
Skewness-0.052264062
Sum-9856.4484
Variance3.9376331
MonotonicityNot monotonic
2025-05-06T10:02:05.614458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-2.918825875 2
 
< 0.1%
-1.398313896 2
 
< 0.1%
1.317227982 2
 
< 0.1%
-0.0812448591 2
 
< 0.1%
0.8272606735 2
 
< 0.1%
2.791584777 2
 
< 0.1%
2.495416812 2
 
< 0.1%
0.1848572767 2
 
< 0.1%
1.984655573 2
 
< 0.1%
-1.782314906 2
 
< 0.1%
Other values (9694) 9787
96.9%
(Missing) 298
 
2.9%
ValueCountFrequency (%)
-9.526822971 2
< 0.1%
-9.484999764 1
< 0.1%
-8.940163554 1
< 0.1%
-8.516383063 1
< 0.1%
-8.397873567 1
< 0.1%
-7.781055511 1
< 0.1%
-7.672901052 1
< 0.1%
-7.656514677 1
< 0.1%
-7.613069694 1
< 0.1%
-7.601025388 1
< 0.1%
ValueCountFrequency (%)
8.418082068 1
< 0.1%
7.894641247 1
< 0.1%
7.474779184 1
< 0.1%
7.265099752 1
< 0.1%
6.952941933 1
< 0.1%
6.536874204 1
< 0.1%
6.495791076 1
< 0.1%
5.920896739 1
< 0.1%
5.889248898 1
< 0.1%
5.832009925 1
< 0.1%

num15
Real number (ℝ)

Missing 

Distinct9690
Distinct (%)98.9%
Missing312
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean0.7325334
Minimum-16.192978
Maximum20.361367
Zeros0
Zeros (%)0.0%
Negative4653
Negative (%)46.0%
Memory size79.1 KiB
2025-05-06T10:02:05.688167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-16.192978
5-th percentile-6.7309249
Q1-2.6982109
median0.35370715
Q33.9715466
95-th percentile9.3717675
Maximum20.361367
Range36.554345
Interquartile range (IQR)6.6697576

Descriptive statistics

Standard deviation4.8945083
Coefficient of variation (CV)6.6816179
Kurtosis-0.0444489
Mean0.7325334
Median Absolute Deviation (MAD)3.3115752
Skewness0.29938455
Sum7173.6996
Variance23.956212
MonotonicityNot monotonic
2025-05-06T10:02:05.757941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-7.413568593 2
 
< 0.1%
12.35098251 2
 
< 0.1%
-7.024552412 2
 
< 0.1%
-1.424713101 2
 
< 0.1%
-3.227948152 2
 
< 0.1%
7.182836196 2
 
< 0.1%
-1.46732714 2
 
< 0.1%
12.62266141 2
 
< 0.1%
6.368036703 2
 
< 0.1%
0.2569865474 2
 
< 0.1%
Other values (9680) 9773
96.7%
(Missing) 312
 
3.1%
ValueCountFrequency (%)
-16.19297775 1
< 0.1%
-15.28308016 1
< 0.1%
-14.57428056 1
< 0.1%
-14.44851691 1
< 0.1%
-13.59223492 1
< 0.1%
-13.16721195 1
< 0.1%
-13.16579672 1
< 0.1%
-12.90561264 1
< 0.1%
-12.63828248 1
< 0.1%
-12.56721382 1
< 0.1%
ValueCountFrequency (%)
20.36136712 1
< 0.1%
18.99294776 1
< 0.1%
17.73103524 1
< 0.1%
17.69777445 1
< 0.1%
17.14007603 1
< 0.1%
16.67936275 1
< 0.1%
16.66073097 1
< 0.1%
16.54440652 1
< 0.1%
16.52379036 1
< 0.1%
16.40036541 1
< 0.1%

num16
Real number (ℝ)

Missing 

Distinct9696
Distinct (%)99.0%
Missing311
Missing (%)3.1%
Infinite0
Infinite (%)0.0%
Mean1.3266149
Minimum-20.598413
Maximum22.350053
Zeros0
Zeros (%)0.0%
Negative3972
Negative (%)39.3%
Memory size79.1 KiB
2025-05-06T10:02:05.831124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-20.598413
5-th percentile-7.8141383
Q1-2.3673835
median1.3852986
Q35.1269223
95-th percentile10.182144
Maximum22.350053
Range42.948465
Interquartile range (IQR)7.4943058

Descriptive statistics

Standard deviation5.5083982
Coefficient of variation (CV)4.1522208
Kurtosis0.0043031935
Mean1.3266149
Median Absolute Deviation (MAD)3.7453865
Skewness-0.066354062
Sum12992.867
Variance30.34245
MonotonicityNot monotonic
2025-05-06T10:02:05.912327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01851002945 2
 
< 0.1%
0.4346819733 2
 
< 0.1%
-4.27980027 2
 
< 0.1%
-6.486828589 2
 
< 0.1%
-2.94863321 2
 
< 0.1%
3.953906269 2
 
< 0.1%
3.702844262 2
 
< 0.1%
4.079280644 2
 
< 0.1%
6.737172814 2
 
< 0.1%
-7.842703303 2
 
< 0.1%
Other values (9686) 9774
96.7%
(Missing) 311
 
3.1%
ValueCountFrequency (%)
-20.59841262 1
< 0.1%
-20.44159541 1
< 0.1%
-19.72176301 1
< 0.1%
-19.21178409 1
< 0.1%
-17.65802855 1
< 0.1%
-17.64007118 1
< 0.1%
-17.51743807 1
< 0.1%
-16.86381853 1
< 0.1%
-16.52966572 1
< 0.1%
-16.37877735 1
< 0.1%
ValueCountFrequency (%)
22.35005258 1
< 0.1%
21.99904929 1
< 0.1%
20.84569068 1
< 0.1%
20.60062712 1
< 0.1%
19.83743858 1
< 0.1%
19.40582996 1
< 0.1%
18.74629829 1
< 0.1%
18.18903662 1
< 0.1%
18.14937734 1
< 0.1%
17.89595153 1
< 0.1%

num17
Real number (ℝ)

Missing 

Distinct9706
Distinct (%)99.0%
Missing301
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean2.1426885
Minimum-18.054041
Maximum23.913896
Zeros0
Zeros (%)0.0%
Negative2917
Negative (%)28.9%
Memory size79.1 KiB
2025-05-06T10:02:05.979473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-18.054041
5-th percentile-6.020152
Q1-0.66844928
median2.4576566
Q35.1942996
95-th percentile9.1775134
Maximum23.913896
Range41.967937
Interquartile range (IQR)5.8627489

Descriptive statistics

Standard deviation4.6704686
Coefficient of variation (CV)2.1797236
Kurtosis0.61181997
Mean2.1426885
Median Absolute Deviation (MAD)2.9176279
Skewness-0.21223581
Sum21006.918
Variance21.813277
MonotonicityNot monotonic
2025-05-06T10:02:06.050132image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.663140713 2
 
< 0.1%
0.2195040116 2
 
< 0.1%
-8.833875706 2
 
< 0.1%
-0.7614253846 2
 
< 0.1%
5.329560424 2
 
< 0.1%
6.656362437 2
 
< 0.1%
2.729906991 2
 
< 0.1%
4.204013936 2
 
< 0.1%
1.453255103 2
 
< 0.1%
-4.170890406 2
 
< 0.1%
Other values (9696) 9784
96.8%
(Missing) 301
 
3.0%
ValueCountFrequency (%)
-18.05404065 1
< 0.1%
-17.8920553 1
< 0.1%
-17.49595652 1
< 0.1%
-15.62561879 1
< 0.1%
-15.50433068 1
< 0.1%
-15.42111707 1
< 0.1%
-14.8946942 1
< 0.1%
-14.0852508 1
< 0.1%
-13.96742338 1
< 0.1%
-13.91851249 1
< 0.1%
ValueCountFrequency (%)
23.91389614 1
< 0.1%
22.24200993 1
< 0.1%
22.02429 1
< 0.1%
20.19742853 1
< 0.1%
19.69544598 1
< 0.1%
19.67639532 1
< 0.1%
19.35090096 1
< 0.1%
18.97916022 1
< 0.1%
18.95555326 1
< 0.1%
18.60480077 1
< 0.1%

num18
Real number (ℝ)

Missing 

Distinct9701
Distinct (%)99.0%
Missing302
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean1.6596293
Minimum-15.162432
Maximum18.228559
Zeros0
Zeros (%)0.0%
Negative3739
Negative (%)37.0%
Memory size79.1 KiB
2025-05-06T10:02:06.114230image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-15.162432
5-th percentile-6.4934365
Q1-1.9132946
median1.542463
Q35.1846111
95-th percentile9.9618937
Maximum18.228559
Range33.390991
Interquartile range (IQR)7.0979058

Descriptive statistics

Standard deviation5.0297342
Coefficient of variation (CV)3.0306372
Kurtosis-0.30098007
Mean1.6596293
Median Absolute Deviation (MAD)3.5498061
Skewness0.065286735
Sum16269.346
Variance25.298227
MonotonicityNot monotonic
2025-05-06T10:02:06.195223image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.878633034 2
 
< 0.1%
-1.334353228 2
 
< 0.1%
3.655165731 2
 
< 0.1%
0.5383406679 2
 
< 0.1%
-5.985157784 2
 
< 0.1%
-3.987006856 2
 
< 0.1%
-1.783224624 2
 
< 0.1%
1.01557427 2
 
< 0.1%
-3.259314245 2
 
< 0.1%
-7.108829144 2
 
< 0.1%
Other values (9691) 9783
96.8%
(Missing) 302
 
3.0%
ValueCountFrequency (%)
-15.16243225 1
< 0.1%
-14.31256596 1
< 0.1%
-13.80654023 1
< 0.1%
-13.42108101 1
< 0.1%
-13.31970281 2
< 0.1%
-13.01661989 1
< 0.1%
-12.87367779 1
< 0.1%
-12.80192208 1
< 0.1%
-12.63405032 1
< 0.1%
-12.5660131 1
< 0.1%
ValueCountFrequency (%)
18.22855906 1
< 0.1%
17.42362983 1
< 0.1%
17.31283452 1
< 0.1%
17.1351534 1
< 0.1%
17.08676032 1
< 0.1%
17.0579445 1
< 0.1%
17.05647579 1
< 0.1%
16.95491117 1
< 0.1%
16.78613943 1
< 0.1%
16.74437735 1
< 0.1%

num19
Real number (ℝ)

Missing 

Distinct9699
Distinct (%)99.0%
Missing305
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean-0.0030084299
Minimum-3.6253212
Maximum3.3811621
Zeros0
Zeros (%)0.0%
Negative4926
Negative (%)48.7%
Memory size79.1 KiB
2025-05-06T10:02:06.266593image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-3.6253212
5-th percentile-1.6325925
Q1-0.67349615
median-0.006071706
Q30.67118131
95-th percentile1.6233093
Maximum3.3811621
Range7.0064833
Interquartile range (IQR)1.3446775

Descriptive statistics

Standard deviation0.99803781
Coefficient of variation (CV)-331.74707
Kurtosis-0.0093300496
Mean-0.0030084299
Median Absolute Deviation (MAD)0.67264263
Skewness-0.0020524707
Sum-29.482613
Variance0.99607948
MonotonicityNot monotonic
2025-05-06T10:02:06.338307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1255822774 2
 
< 0.1%
-1.492326743 2
 
< 0.1%
-0.1129605582 2
 
< 0.1%
2.274648315 2
 
< 0.1%
1.13371189 2
 
< 0.1%
-0.6312239801 2
 
< 0.1%
1.181802976 2
 
< 0.1%
0.7105920556 2
 
< 0.1%
-0.6501520733 2
 
< 0.1%
-0.8527078845 2
 
< 0.1%
Other values (9689) 9780
96.8%
(Missing) 305
 
3.0%
ValueCountFrequency (%)
-3.625321189 1
< 0.1%
-3.51567551 1
< 0.1%
-3.493494586 1
< 0.1%
-3.472473222 1
< 0.1%
-3.28587291 1
< 0.1%
-3.239675919 1
< 0.1%
-3.238773471 1
< 0.1%
-3.22856814 1
< 0.1%
-3.156030736 1
< 0.1%
-3.079765411 1
< 0.1%
ValueCountFrequency (%)
3.381162106 1
< 0.1%
3.341559533 1
< 0.1%
3.274168059 1
< 0.1%
3.268132497 1
< 0.1%
3.251263447 1
< 0.1%
3.244777151 1
< 0.1%
3.232734584 1
< 0.1%
3.192355501 1
< 0.1%
3.182887013 1
< 0.1%
3.030241188 1
< 0.1%

num20
Real number (ℝ)

Missing 

Distinct9713
Distinct (%)99.0%
Missing291
Missing (%)2.9%
Infinite0
Infinite (%)0.0%
Mean0.0064280368
Minimum-3.5853716
Maximum3.9465158
Zeros0
Zeros (%)0.0%
Negative4923
Negative (%)48.7%
Memory size79.1 KiB
2025-05-06T10:02:06.411134image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-3.5853716
5-th percentile-1.6161031
Q1-0.65510484
median-0.0040336596
Q30.68662379
95-th percentile1.6368244
Maximum3.9465158
Range7.5318874
Interquartile range (IQR)1.3417286

Descriptive statistics

Standard deviation0.99234886
Coefficient of variation (CV)154.37822
Kurtosis0.018602656
Mean0.0064280368
Median Absolute Deviation (MAD)0.66734082
Skewness0.0092010784
Sum63.084753
Variance0.98475626
MonotonicityNot monotonic
2025-05-06T10:02:06.488369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.284198317 2
 
< 0.1%
-1.99349708 2
 
< 0.1%
0.3576142504 2
 
< 0.1%
0.5570779622 2
 
< 0.1%
-1.024911217 2
 
< 0.1%
0.7406665123 2
 
< 0.1%
-0.533264976 2
 
< 0.1%
0.513378872 2
 
< 0.1%
-0.2950207068 2
 
< 0.1%
-0.6980272511 2
 
< 0.1%
Other values (9703) 9794
96.9%
(Missing) 291
 
2.9%
ValueCountFrequency (%)
-3.585371635 1
< 0.1%
-3.506218571 1
< 0.1%
-3.331166816 1
< 0.1%
-3.329043592 1
< 0.1%
-3.267446857 1
< 0.1%
-3.260532527 1
< 0.1%
-3.201011246 1
< 0.1%
-3.198992452 1
< 0.1%
-3.150061153 1
< 0.1%
-3.126312081 1
< 0.1%
ValueCountFrequency (%)
3.946515813 1
< 0.1%
3.876123486 1
< 0.1%
3.736763724 1
< 0.1%
3.716614472 1
< 0.1%
3.493595043 1
< 0.1%
3.489841734 1
< 0.1%
3.262002796 1
< 0.1%
3.255442913 1
< 0.1%
3.178997237 1
< 0.1%
3.171516926 1
< 0.1%

cat1
Categorical

Missing 

Distinct5
Distinct (%)0.1%
Missing324
Missing (%)3.2%
Memory size521.7 KiB
cat
3940 
dog
3410 
rabbit
1018 
parrot
958 
turtle
455 

Length

Max length6
Median length3
Mean length3.7456293
Min length3

Characters and Unicode

Total characters36636
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowturtle
2nd rowdog
3rd rowdog
4th rowdog
5th rowparrot

Common Values

ValueCountFrequency (%)
cat 3940
39.0%
dog 3410
33.7%
rabbit 1018
 
10.1%
parrot 958
 
9.5%
turtle 455
 
4.5%
(Missing) 324
 
3.2%

Length

2025-05-06T10:02:06.559984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-06T10:02:06.616594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
cat 3940
40.3%
dog 3410
34.9%
rabbit 1018
 
10.4%
parrot 958
 
9.8%
turtle 455
 
4.7%

Most occurring characters

ValueCountFrequency (%)
t 6826
18.6%
a 5916
16.1%
o 4368
11.9%
c 3940
10.8%
d 3410
9.3%
g 3410
9.3%
r 3389
9.3%
b 2036
 
5.6%
i 1018
 
2.8%
p 958
 
2.6%
Other values (3) 1365
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36636
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 6826
18.6%
a 5916
16.1%
o 4368
11.9%
c 3940
10.8%
d 3410
9.3%
g 3410
9.3%
r 3389
9.3%
b 2036
 
5.6%
i 1018
 
2.8%
p 958
 
2.6%
Other values (3) 1365
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36636
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 6826
18.6%
a 5916
16.1%
o 4368
11.9%
c 3940
10.8%
d 3410
9.3%
g 3410
9.3%
r 3389
9.3%
b 2036
 
5.6%
i 1018
 
2.8%
p 958
 
2.6%
Other values (3) 1365
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36636
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 6826
18.6%
a 5916
16.1%
o 4368
11.9%
c 3940
10.8%
d 3410
9.3%
g 3410
9.3%
r 3389
9.3%
b 2036
 
5.6%
i 1018
 
2.8%
p 958
 
2.6%
Other values (3) 1365
 
3.7%

cat2
Categorical

Missing 

Distinct15
Distinct (%)0.2%
Missing277
Missing (%)2.7%
Memory size547.2 KiB
microwave
706 
laptop
690 
dvdplayer
674 
bed
666 
phone
660 
Other values (10)
6432 

Length

Max length13
Median length9
Mean length6.4216524
Min length2

Characters and Unicode

Total characters63112
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowfridge
2nd rowsofa
3rd rowbookshelf
4th rowchair
5th rowlaptop

Common Values

ValueCountFrequency (%)
microwave 706
 
7.0%
laptop 690
 
6.8%
dvdplayer 674
 
6.7%
bed 666
 
6.6%
phone 660
 
6.5%
fridge 659
 
6.5%
table 656
 
6.5%
lamp 654
 
6.5%
clothshelf 653
 
6.5%
bookshelf 651
 
6.4%
Other values (5) 3159
31.3%

Length

2025-05-06T10:02:06.687739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
microwave 706
 
7.2%
laptop 690
 
7.0%
dvdplayer 674
 
6.9%
bed 666
 
6.8%
phone 660
 
6.7%
fridge 659
 
6.7%
table 656
 
6.7%
lamp 654
 
6.7%
clothshelf 653
 
6.6%
bookshelf 651
 
6.6%
Other values (5) 3159
32.1%

Most occurring characters

ValueCountFrequency (%)
e 6589
 
10.4%
a 5899
 
9.3%
l 5263
 
8.3%
o 5261
 
8.3%
r 5260
 
8.3%
p 3368
 
5.3%
c 3274
 
5.2%
h 3268
 
5.2%
d 2673
 
4.2%
i 2662
 
4.2%
Other values (14) 19595
31.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 63112
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 6589
 
10.4%
a 5899
 
9.3%
l 5263
 
8.3%
o 5261
 
8.3%
r 5260
 
8.3%
p 3368
 
5.3%
c 3274
 
5.2%
h 3268
 
5.2%
d 2673
 
4.2%
i 2662
 
4.2%
Other values (14) 19595
31.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 63112
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 6589
 
10.4%
a 5899
 
9.3%
l 5263
 
8.3%
o 5261
 
8.3%
r 5260
 
8.3%
p 3368
 
5.3%
c 3274
 
5.2%
h 3268
 
5.2%
d 2673
 
4.2%
i 2662
 
4.2%
Other values (14) 19595
31.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 63112
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 6589
 
10.4%
a 5899
 
9.3%
l 5263
 
8.3%
o 5261
 
8.3%
r 5260
 
8.3%
p 3368
 
5.3%
c 3274
 
5.2%
h 3268
 
5.2%
d 2673
 
4.2%
i 2662
 
4.2%
Other values (14) 19595
31.0%

cat3
Categorical

Missing 

Distinct20
Distinct (%)0.2%
Missing310
Missing (%)3.1%
Memory size552.8 KiB
shchi
1994 
kasha
1491 
borscht
963 
olivier
962 
ukha
472 
Other values (15)
3913 

Length

Max length18
Median length8
Mean length7.002246
Min length4

Characters and Unicode

Total characters68587
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowokroshka
2nd rowshchi
3rd rowpelmeni
4th rowsashlyk
5th rowsashlyk

Common Values

ValueCountFrequency (%)
shchi 1994
19.7%
kasha 1491
14.8%
borscht 963
9.5%
olivier 962
9.5%
ukha 472
 
4.7%
solyanka 456
 
4.5%
pelmeni 454
 
4.5%
okroshka 388
 
3.8%
bliny 386
 
3.8%
seledka pod shuboi 380
 
3.8%
Other values (10) 1849
18.3%
(Missing) 310
 
3.1%

Length

2025-05-06T10:02:06.754653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
shchi 1994
18.4%
kasha 1491
13.7%
borscht 963
 
8.9%
olivier 962
 
8.9%
ukha 472
 
4.3%
solyanka 456
 
4.2%
pelmeni 454
 
4.2%
okroshka 388
 
3.6%
bliny 386
 
3.6%
pod 380
 
3.5%
Other values (13) 2916
26.8%

Most occurring characters

ValueCountFrequency (%)
h 8254
12.0%
s 7122
10.4%
i 7060
10.3%
a 6216
9.1%
e 5029
 
7.3%
k 4826
 
7.0%
o 4408
 
6.4%
l 3547
 
5.2%
r 3467
 
5.1%
c 3264
 
4.8%
Other values (13) 15394
22.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 68587
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
h 8254
12.0%
s 7122
10.4%
i 7060
10.3%
a 6216
9.1%
e 5029
 
7.3%
k 4826
 
7.0%
o 4408
 
6.4%
l 3547
 
5.2%
r 3467
 
5.1%
c 3264
 
4.8%
Other values (13) 15394
22.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 68587
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
h 8254
12.0%
s 7122
10.4%
i 7060
10.3%
a 6216
9.1%
e 5029
 
7.3%
k 4826
 
7.0%
o 4408
 
6.4%
l 3547
 
5.2%
r 3467
 
5.1%
c 3264
 
4.8%
Other values (13) 15394
22.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 68587
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
h 8254
12.0%
s 7122
10.4%
i 7060
10.3%
a 6216
9.1%
e 5029
 
7.3%
k 4826
 
7.0%
o 4408
 
6.4%
l 3547
 
5.2%
r 3467
 
5.1%
c 3264
 
4.8%
Other values (13) 15394
22.4%

date
Date

Missing 

Distinct495
Distinct (%)5.0%
Missing251
Missing (%)2.5%
Memory size79.1 KiB
Minimum2024-01-01 00:00:00
Maximum2025-05-09 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-06T10:02:06.818122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-06T10:02:06.899198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

class
Categorical

Missing 

Distinct2
Distinct (%)< 0.1%
Missing303
Missing (%)3.0%
Memory size514.5 KiB
0.0
7831 
1.0
1971 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters29406
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 7831
77.5%
1.0 1971
 
19.5%
(Missing) 303
 
3.0%

Length

2025-05-06T10:02:06.965551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-06T10:02:07.002123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0.0 7831
79.9%
1.0 1971
 
20.1%

Most occurring characters

ValueCountFrequency (%)
0 17633
60.0%
. 9802
33.3%
1 1971
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 29406
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 17633
60.0%
. 9802
33.3%
1 1971
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 29406
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 17633
60.0%
. 9802
33.3%
1 1971
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 29406
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 17633
60.0%
. 9802
33.3%
1 1971
 
6.7%

Interactions

Correlations

2025-05-06T10:02:07.144102image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
cat1cat2cat3classnum1num10num11num12num13num14num15num16num17num18num19num2num20num3num4num5num6num7num8num9
cat11.0000.0240.0260.0000.0000.0180.0100.0040.0000.0080.0000.0120.0170.0020.0000.0000.0000.0220.0000.0190.0000.0000.0000.000
cat20.0241.0000.0000.0320.0030.0000.0000.0000.0100.0000.0000.0140.0020.0100.0200.0000.0000.0050.0180.0090.0000.0080.0100.000
cat30.0260.0001.0000.0200.0200.0070.0000.0160.0000.0000.0160.0000.0000.0140.0080.0000.0000.0000.0000.0000.0100.0120.0110.000
class0.0000.0320.0201.0000.0170.0310.1470.1850.0390.0790.0760.2260.1890.1430.0000.1850.0150.0000.0000.0280.0450.0670.1600.000
num10.0000.0030.0200.0171.0000.128-0.203-0.0650.042-0.2680.412-0.3700.4000.5270.0010.035-0.002-0.1100.277-0.2130.2110.1370.011-0.295
num100.0180.0000.0070.0310.1281.0000.1060.005-0.1410.0210.1470.398-0.1870.119-0.0050.0570.0050.007-0.181-0.116-0.381-0.2490.061-0.136
num110.0100.0000.0000.147-0.2030.1061.0000.0480.209-0.287-0.1920.1250.211-0.3590.009-0.0970.012-0.115-0.1700.052-0.229-0.131-0.1070.092
num120.0040.0000.0160.185-0.0650.0050.0481.000-0.1040.142-0.435-0.177-0.453-0.631-0.014-0.1540.002-0.135-0.2000.140-0.068-0.213-0.0840.150
num130.0000.0100.0000.0390.042-0.1410.209-0.1041.0000.072-0.255-0.1900.1810.1870.000-0.0070.0090.2230.1460.0130.0500.0100.1100.053
num140.0080.0000.0000.079-0.2680.021-0.2870.1420.0721.000-0.1720.044-0.551-0.141-0.008-0.0650.0040.2020.0710.049-0.081-0.1620.2730.035
num150.0000.0000.0160.0760.4120.147-0.192-0.435-0.255-0.1721.0000.0240.3950.4550.010-0.021-0.0170.1320.3870.2710.2480.403-0.227-0.197
num160.0120.0140.0000.226-0.3700.3980.125-0.177-0.1900.0440.0241.000-0.228-0.1990.0060.277-0.0040.225-0.2410.204-0.571-0.434-0.3820.183
num170.0170.0020.0000.1890.400-0.1870.211-0.4530.181-0.5510.395-0.2281.0000.5760.0180.366-0.0050.0990.3060.0330.2000.5480.107-0.048
num180.0020.0100.0140.1430.5270.119-0.359-0.6310.187-0.1410.455-0.1990.5761.0000.0150.371-0.0090.1020.557-0.2240.2720.3180.287-0.350
num190.0000.0200.0080.0000.001-0.0050.009-0.0140.000-0.0080.0100.0060.0180.0151.0000.0050.0100.0060.0090.006-0.0100.0030.0070.006
num20.0000.0000.0000.1850.0350.057-0.097-0.154-0.007-0.065-0.0210.2770.3660.3710.0051.0000.006-0.0490.0810.103-0.0670.2250.075-0.035
num200.0000.0000.0000.015-0.0020.0050.0120.0020.0090.004-0.017-0.004-0.005-0.0090.0100.0061.000-0.003-0.015-0.013-0.0060.0040.0070.010
num30.0220.0050.0000.000-0.1100.007-0.115-0.1350.2230.2020.1320.2250.0990.1020.006-0.049-0.0031.0000.0490.060-0.115-0.1160.087-0.047
num40.0000.0180.0000.0000.277-0.181-0.170-0.2000.1460.0710.387-0.2410.3060.5570.0090.081-0.0150.0491.000-0.0260.3300.117-0.050-0.217
num50.0190.0090.0000.028-0.213-0.1160.0520.1400.0130.0490.2710.2040.033-0.2240.0060.103-0.0130.060-0.0261.0000.0860.102-0.0640.084
num60.0000.0000.0100.0450.211-0.381-0.229-0.0680.050-0.0810.248-0.5710.2000.272-0.010-0.067-0.006-0.1150.3300.0861.0000.209-0.024-0.081
num70.0000.0080.0120.0670.137-0.249-0.131-0.2130.010-0.1620.403-0.4340.5480.3180.0030.2250.004-0.1160.1170.1020.2091.0000.1330.076
num80.0000.0100.0110.1600.0110.061-0.107-0.0840.1100.273-0.227-0.3820.1070.2870.0070.0750.0070.087-0.050-0.064-0.0240.1331.000-0.346
num90.0000.0000.0000.000-0.295-0.1360.0920.1500.0530.035-0.1970.183-0.048-0.3500.006-0.0350.010-0.047-0.2170.084-0.0810.076-0.3461.000

Missing values

2025-05-06T10:02:02.677948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-06T10:02:02.806741image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-05-06T10:02:03.022148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

num1num2num3num4num5num6num7num8num9num10num11num12num13num14num15num16num17num18num19num20cat1cat2cat3dateclass
0-1.404142NaN1.788323-0.3005260.793042-0.070519-1.411121-0.0360980.907675-0.9941830.027012-0.2564101.762716-2.037465-2.9284501.7626501.225417-0.439977-1.346332-0.242933turtlefridgeokroshka2024-03-290.0
11.3380513.7892880.890730-2.530025-0.687945-1.156679-1.396976NaN0.594488NaN-0.6258263.5419380.210295-1.696082-4.0401764.360851-0.0446941.225835-0.103230-0.343715dogsofashchi2025-05-040.0
2-2.6541842.5513781.246405-1.9302321.386073-0.5924110.0136080.2485713.8977120.288660-2.7493484.222056-1.3878601.333214-5.4093693.333748-4.089768-4.7467330.405331-1.603466dogbookshelfpelmeni2024-10-060.0
3-1.996824-4.9226711.613875-0.521229-1.8334481.650557-4.951148-1.8057100.284719-3.726858-0.8795982.3576031.5062042.243788-8.056116-2.255363-10.493229-8.7732960.8803040.700649dogchairsashlyk2025-01-310.0
4-1.1443920.4135490.3178971.1124102.277326-3.058738-1.160673-4.4181401.4869354.9875432.365770-0.5135771.408904-1.5349495.30896412.455026-0.9178520.208427-0.126446-1.707781parrotlaptopsashlyk2025-01-080.0
5-4.358914-0.3936370.716674-2.1312307.275852-2.846576-1.645392-1.6825254.252925-0.5749011.1984850.4890571.347844-0.933174NaN12.161208-1.928509-7.925017-0.369569-0.741254dogsofaNaN2024-06-040.0
6-0.7699710.9614131.846254-1.2415921.876595-2.490238-3.465597-1.8028892.2197013.7517800.2963603.0000751.735166-0.855191-3.2244269.398515-3.122999-2.6341451.357434-0.659161catsofapickled vegetables2024-08-190.0
72.2853753.564407-1.950064-3.410126-1.5676991.478155-2.242138-0.540703-0.2514490.6140990.9511473.585911-0.563038NaN-7.957929-1.0577810.754069-2.139531-0.8890270.125123catclothshelfseledka pod shuboi2025-01-260.0
81.2474843.163106-1.0359380.919867-2.729044-1.3093882.718491-3.192852-0.137032-0.1993054.338643-0.623777-2.505276-3.4665412.8715451.4491508.8734690.745208-1.2569870.691152catfridgekasha2024-01-150.0
91.1067265.098006-2.7863990.3116730.246183-3.294238-0.7654771.0413500.3246781.7218255.1126540.555955-0.481383-3.660236-4.8567834.6207158.9543611.915868-0.1787021.362284catNaNkasha2025-04-290.0
num1num2num3num4num5num6num7num8num9num10num11num12num13num14num15num16num17num18num19num20cat1cat2cat3dateclass
100952.751844-0.6222510.5867631.591745-2.7861481.5549760.550217-0.7052760.497426-1.891485-1.025028-0.335747-3.211569-3.2147962.765255-4.5911256.4204683.186056-0.9627000.054831rabbitdvdplayerNaNNaN1.0
100961.660325-2.212526-2.166043-5.8601871.6715613.7803012.2417185.436736-0.8230260.818438-1.528787-0.6714282.375987-1.546524-1.920923-11.5410270.7388271.721352-0.118188-0.531589catbedborscht2025-04-151.0
100972.782602-2.8983971.042872-2.7174710.2650585.273483-3.5823622.129112-2.3312924.1448823.835348NaN-1.569546-2.2567505.464311-1.9010604.0684912.492772-0.4702040.012353rabbitvacuumcleanerolivier2024-11-101.0
100980.7154470.264612-2.065058-2.0143502.0610604.0578570.0268501.2406871.6054520.289857-1.5877840.9721271.874551-2.223179-2.547665-4.9311340.5306741.659497-0.205572-0.259005parrotphonebliny2025-02-281.0
100992.7780402.7893902.529903-3.2831221.175829-1.1299992.0584571.671408-3.6197951.562650-2.264500-0.7842445.186565-0.3470240.575500-0.2397572.8378745.745436-0.442453-0.194271catfridgepelmeni2024-02-141.0
101000.458981-1.9162230.161379-4.0228844.8501120.704363-1.8771701.3530200.6830354.7790531.7114011.5847153.4314510.7688851.1364262.270862-3.671986-3.0680300.276662-1.061066rabbitbedvinegret2024-10-291.0
101012.719239-0.104002NaN1.202461-2.6125782.117033-1.390512-1.954045-1.5865060.3833990.670899-1.048861-1.602645-2.6084734.8440570.3943045.8985564.0127680.839983-0.355717parrotlampokroshka2024-02-071.0
101022.808701-0.789768-0.479053-1.8625661.0666020.0615952.510577-0.3269983.566594-2.608572-2.051744-0.0559972.708209-5.547736-0.876046-5.2421617.8536112.4105960.8012130.869559dogmicrowavekasha2024-04-191.0
10103-1.348852-0.9933841.9794110.0770764.2515311.700839-1.4433902.448801-1.884344-1.1318602.3658000.284989NaN-0.690482-1.748947-1.6027282.458221-0.986676-0.558675-0.078621rabbitbookshelfpelmeni2024-04-071.0
101040.433487-4.727681-4.175153-3.303115-0.090450-1.2539250.445071-0.7392331.5263571.1845681.0201333.347142-2.484015-1.888805-1.300213-4.899535-5.414314-8.7972620.8527530.284470rabbitTVholodets2024-01-241.0

Duplicate rows

Most frequently occurring

num1num2num3num4num5num6num7num8num9num10num11num12num13num14num15num16num17num18num19num20cat1cat2cat3dateclass# duplicates
0-5.838786-0.9309442.0245301.654022-2.471982NaN-2.411700-2.2194230.3992634.8876441.4704343.0828405.6333664.134514-7.9188804.563048-13.529462-3.429726-0.3111840.317472NaNfridgepryaniki2024-05-011.02
1-4.0242881.2845380.153332-3.5250230.231924-0.7888251.442171-1.3042735.3200371.289214-3.3877633.368415-3.0351682.796736-3.2204124.630775-8.829087-7.349458-1.4210101.594170catTVpryaniki2025-03-090.02
2-3.796176-1.6093733.2795590.5456533.804992-1.580554-0.5879290.6028132.5892371.237712-3.6558221.2146131.9889812.4954170.2849205.552970-6.565343-1.735531-1.142494-0.305546dogbookshelfpryaniki2024-11-130.02
3-3.7620700.867374-0.669076-0.419098NaN-2.527258-0.2797682.141408-1.1990950.3442083.667820-1.628674-0.1383810.827261-1.1643885.9466450.304058-2.9710621.2235691.306012catclothshelfpryaniki2024-03-210.02
4-3.7108721.9750352.808067-0.3511922.6711630.114130-0.2026260.8368611.137951-3.0233841.9071610.4902002.7435340.478229-5.3405012.7016142.328249-3.402292-0.929117NaNNaNclothshelfpryaniki2024-05-08NaN2
5-3.296367-1.2036231.254461-2.9271333.445069-2.827958-2.529988-1.9113161.449202-0.6965513.4447450.918869-1.361183-0.238707-1.4121699.825599-2.543278-10.6499961.1965390.757880dogfridgepryaniki2024-02-180.02
6-3.1839620.4250191.5693990.9965701.8481361.627678-1.9986070.712190-0.902899-5.3267100.7572183.1184982.2460242.791585-8.454748-2.609587-3.781343-7.056191-0.1342720.071469catbedpryaniki2024-10-280.02
7-2.8830280.6151913.598226-4.398030NaN1.014351-0.955741-0.1242042.9769011.816772-1.7056631.7320312.6059051.317228-2.581295NaNNaN-3.987007-0.7717520.513379turtlelamppryaniki2024-09-280.02
8-2.8659911.0833781.328027-2.7894512.128359-0.413682-0.430348-3.6246857.009912-3.483627-1.6444526.516361-1.8168631.351547-6.5156873.702844-5.500158-13.3197030.710592-0.778688catmirrorpryaniki2024-05-100.02
9-2.7258341.200924-1.328011-3.6653412.8030591.006180-0.324547-1.7854793.411511-1.0360743.074316-1.3646801.821308-0.982598-3.014485NaN0.497604-5.011047-0.7547520.898365catlaptoppryaniki2025-02-020.02